Dynamic OCT angiography (OCTA) is an attractive approach for monitoring stimulus-evoked hemodynamics; however, a large dataset poses a great challenge to data processing. This study proposed a GPU-based real-time data processing pipeline for dynamic inverse SNR-decorrelation OCTA (ID-OCTA) with line-process rate of 133 kHz. Real-time processing enabled automatic optimization of angiogram quality, which improved the vessel SNR, contrast-to-noise ratio, and connectivity by 14.37, 14.08, and 9.76%, respectively. Furthermore, dynamic angiographic imaging of stimulus-evoked hemodynamics was achieved within a single trail in the mouse retina. Therefore, GPU ID-OCTA enables real-time and high-quality angiographic imaging and is particularly suitable for hemodynamic studies.
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